Fed Report: PPP Loans Went Disproportionately to High-Income Areas

CLEVELAND – A report by two economists at the Cleveland branch of the Federal Reserve has found that first-round Paycheck Protection Program loans went disproportionately to upper-income areas. 

Though the relief program reached low- and moderate-income communities better than conventional small-business lending, data analyzed by Cleveland Fed vice president Mark Schweitzer and research analyst Garrett Borawski showed “more unevenness in the coverage of PPP lending” to communities made up predominantly of people of color.

In an October report, the Small Business Administration said that 27% of PPP loan dollars were made in low- and moderate-income communities, which is in proportion to the population. The Federal Reserve defines low-income as a family earning less than 50% of an area’s median income, moderate as between 50% and 80%, middle as 81% to 120% and upper as greater than 120%.

While the distribution of PPP loans is an encouraging sign, the authors state, it doesn’t paint the whole picture.

“PPP loan sizes generally grow proportionally with the payroll size, so firms with more employees received larger loans. But the distribution of small businesses is skewed toward companies with fewer employees: While small businesses are defined as companies with anywhere from one to 500 employees, more than half of US small businesses have only one to four employees, according to Census data,” they write. “The vast chunk of remaining small businesses has between five and 49 employees, and only a tiny fraction – 5% – has between 50 and 499 employees. Basing shares on loan amounts places the focus sharply on relatively less common small businesses with more than 50 employees.”

To normalize the data from the SBA, the researchers compared the number of loans made per thousand residents of a census tract. Low-income tracts received 12.9 PPP loans per 1,000 people, while upper-income tracts got 19.6 loans per thousand people. The average tract has roughly 4,500 people, meaning that a having 1.2 fewer loans per thousand people equates to roughly five fewer businesses receiving a PPP loan. With the gap between low-income and upper-income communities, that equates to nearly 28 fewer loans per tract.

Schweitzer and Borawski also note that businesses are not evenly spread among the population. Downtown areas tend to have more businesses than people, while rural areas are more likely to house residents. To account for that distribution, the two compared the share of PPP loans made in each income-level group to the share of small businesses in each category.

“We see there are proportionally fewer businesses in LMI tracts, but the shares of PPP loans going to those tracts were smaller than the shares of businesses in those tracts. This comparison suggests that PPP loans were not provided in proportion to the number of businesses operating in [low- and moderate-income] communities,” they say.

The authors also examined how the Paycheck Protection Program performed in terms of the race and ethnicity of loan recipients, finding that businesses in majority Asian tracts – especially those in low- and moderate-income tracts – received more PPP loans per thousand people than other groups.

“This reflects higher rates of PPP lending in the census tracts not shown—census tracts that either are majority white or are more demographically diverse and without a racial or ethnic majority,” Borawski and Schweitzer wrote. “In all income categories, census tracts with American Indian or Alaska Native majorities had significantly fewer loans per 1,000 people, indicating that the PPP loan program is likely to have had a lower impact in these communities.”

The full report can be read HERE.

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